NeuroBreak-AI A Cognitive Self-Evolving Framework

"This research paper presents NeuroBreak-AI, an innovative cognitive framework designed to bridge the gap between traditional machine learning models and human-like decision-making processes. In an era where AI often lacks contextual depth, NeuroBreak-AI introduces a self-evolving mechanism that utilizes Advanced Large Language Models (LLMs) and specialized feedback loops to simulate cognitive reasoning. The study details the architecture of the 'Break-Cycle Engine,' which allows the AI to self-correct and adapt its logic based on environmental variables and user interaction. By integrating these cognitive layers, the research demonstrates a significant improvement in the AI's ability to handle complex, non-linear problems compared to standard predictive models. This framework serves as a foundation for more transparent, reliable, and 'human-centric' artificial intelligence systems in professional and personal environments." Artificial Intelligence, Cognitive Computing, Self-Evolving AI, NeuroBreak-AI, Machine Learning, Human-Centric AI, NLP

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-29
DOI
https://doi.org/10.5281/zenodo.18411438
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00
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article

NeuroBreak-AI A Cognitive Self-Evolving Framework

Raj Akshat
Zenodo (CERN European Organization for Nuclear Research)
Explainable Artificial Intelligence (XAI)
article

NeuroBreak-AI A Cognitive Self-Evolving Framework

Raj Akshat
article en

Abstract

No abstract available for this paper.

Zenodo (CERN European Organization for Nuclear Research)
Chhattisgarh Swami Vivekanand Technical University (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 72%
Explainable Artificial Intelligence (XAI)
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